How post-industrial capitalism and a new type of big data will save the planet

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We need transparency, accountability and trust to govern the world, and Mattereum will deliver it

Our goal is to enable a significant reduction of the environmental and social harms caused by inefficiencies in industrial capitalism. The global challenges posed by climate change and resource scarcity are driven by many factors which include imprecise capital allocation, a financial system with poorly defined boundaries, dependence on polluting energy, and outdated methods of industrial production.

Mattereum is working to solve these problems by creating digital twins material objects and using blockchain smart contracts to transform the way they are traded, owned, and combined, to squeeze out these inefficiencies, and more accurately allocate capital to activities which promote wellbeing.

The problem is vast and twofold: it lies in the way industrial production has been engineered to respond to demand and consumption, to the neglect of investment and the disposal of objects at the end of their lifecycle, leading to significant environmental and social harms and trillions in wasted or lost revenue. Mattereum’s supra-industrial approach, using blockchain and other technologies, goes a significant way to solving it.

During the process of developing Mattereum, I began to understand how to weave the threads of our global malaise into a single story, going all the way back to the environmental policy work I did at the Rocky Mountain Institute (RMI) 15 years ago. Since Ethereum launched in 2015, my focus has been on technology, and there were a couple of years back then when my humanitarian and environmental work took a back seat to the immediate need to help the Ethereum team establish our bridgehead — an embassy of the future — on earth today. As we began to work in depth on exactly how Mattereum would be positioned, we knew that the technology must contribute to making the world a measurably better place. But how was always tricky, because without a clear diagnosis, it’s hard to effect a cure.

So as we got closer to launch, it was time to re-examine the analysis I did with the RMI team for the Danish EPA in 2003, A whole systems framework for sustainable production and consumption. The framework was originally developed with UN Sustainable Development Goals funding from Denmark, and was without a doubt a smorgasbord. Its core drive was to go beyond the existing early noughties paradigm on the sustainable Production/Consumption interface to also include sustainable investment at one end of the process, and a very different perspective on waste at the other. Thus creating an “investment, consumption, production, waste” system, modelled as so:

the full IPCW diagram includes a division between natural capital and financial capital, and maps out the ways that waste reduces the efficiency of all the other parts of the system, and models recycling, reuse and reclamation as a separate set of processes.

In this analysis, investment cascades through production systems, through consumption, and into waste, paying for the production of goods or delivering some services along the way. Resource inputs are money — in a properly functioning system more is made than is consumed — and natural capital. The main casualty here is natural capital; most of the time the natural capital is lost, thrown away in the name of financial return. In short, into the machine you pour nature and money, and if you are lucky more money comes out. We don’t even account for the nature that goes into the machine, in most cases. It just gets burned as the price of doing business.

But if we stop the great destructive, over-productive machine of civilization, mass starvation will result. We have a duty to square this circle: to deliver sustainable abundance to all of humanity, and to leave nature alone to its own devices, for the most part. In the future I want to see a self-sustaining closed-loop technosphere (hopefully in orbit… around Proxima Centauri…) and a nature largely left to run wild, which is (more or less) the most productive and environmentally-stabilizing configuration.

I believe that Mattereum, using blockchain smart contracts, finally has the tools to make a modest extension of how capitalism runs — a relatively gentle upgrade — to get a much, much better world very quickly and without having to sacrifice anything we want along the way.

This will not fix everything, but it will double or triple the amount of slack we have to achieve transformation inside of industrial civilization. It may also free up a lot of resources to work on our other problems, too. And it’s a relatively modest plan.

Now, to get full leverage on this, we need two more historical perspectives. So let’s do a little more homework, and get a really solid lock on this aspect of the global problem.

The invention of consumerism is a long, complex story. In essence Sigmund Freud’s nephew, Edward Bernays, weaponizes psychoanalysis to take some of the deep-rooted human needs around identity, sexuality, and religion, and convert them into consistent, persistent, itch-you-can’t-ever-quite-scratch compulsive buying behavior. By coercively deluding us that happiness was to be found in the marketplace, the movement which Bernays came to symbolise has transformed how humans express themselves. In its thrall, we have become a little like the fabled master who loses their keys in the dark, but searches for the keys under the streetlamp “because that’s where the light is.” This process is how we wind up with obsessive shaving of grams off hiking backpacks, and limited edition baseball caps, and a million different car models with 18 cup holders each, all pouring the same poison out the back. Superficial diversity is wrapped around an overwhelming conformity, and a social obligation to consume.

We seem to have taken most of the output of this completely splendiferous industrial and design machinery, and enslaved it to produce the most unimaginably trivial paraphernalia, in gigaton profusion. This is the “horseless carriage” phase of industrial civilization. It’s a production system desperately in need of a better understanding of itself, in service to a people who are increasingly alienated, disoriented, and broke.

Human nature was shaped into consumer identity by people who thought they were advancing civilization by creating markets for industry to serve. Basic drives that could have found many different routes towards self-expression (for example: playing music, athletic achievement, or martial arts) wound up all too frequently channeled into consumerism. It has become an enormous engine for development, but at a price we can no longer afford economically or environmentally.

There is a better way.

True, our civilization does consumer goods really, really well (not so good on important and efficient stuff like preventative health care!) but no consumer goods or combination of consumer goods can resolve the deep psychological impulses to which Bernays and his descendents successfully bound our shopping behavior. Psychological needs cannot ever be fully satisfied by material things. We all know this, but we all play the game (for now).

This is the treadmill. Every step on the treadmill destroys valuable natural resources to satiate human psychological needs that were largely artificially fanned into the flames of consumerism.

Now that we’ve discussed the psychological creation of insatiable demand, let’s talk about the supply side: how are the goods consumed to meet these psychological needs created?

Statistical Process Control: we really do get what we measure, and we measure the wrong things.

Again, I’m going to try and simplify several dozen books’ worth of history into two quick stories.

The first is the invention of the production line. Division of labor started with the manufacturing of pins. Daniel Foote Taylor built the machine that made pins with minimal labour. Adam Smith wrote about it. Division of labor and production lines became a huge phenomenon, truly the engine of industry, and with all that cheap coal power to be had from shallow and open cast mines, the industrial revolution was off to a good start.

But production lines were lossy and buggy for a couple of centuries. Specifically, stuff would go wrong in the machines or in the manual parts of the production lines. At the end of the line, Quality Assurance workers would test sometimes every single object, and a double digit percentage of them would go back up the line for “rework.”

Like bugs in software, somebody had to go and figure out what was wrong with the gadget, and then fix it by hand; debugging for physical production processes. This kind of analysis and labor was routine and endemic in mass production. Finished goods might be 2% defective when they were sold, and big machines were usually built from large collections of parts which were filed down by hand until the pieces fit together well enough to run. Everything looked like integrating low-quality software packages filled with bugs, and trying to build large scale working systems from them. This is probably still going on today in some industries.

For a long time, this was the only kind of mass production we had. In this age — and remember how recent this is for people like high performance car enthusiasts — machines like boats, motorbikes, and scooters were hand-made one-offs, tweaked on the production line until they ran, their collection of imperfect parts hand-tuned until the machine worked as it was supposed to. For the time being. A few parts wear down from use, and then you have to fix it. It was a continuous process of hand-tuning. This is what engineers used to do for a living: hand-tune assemblages of irregular parts into semi-stable machines, constantly fighting against parts wear, metal fatigue, and corrosion. It was hell. Sounds a lot like modern software development, where bitrot and the upgrade cycle are our equivalent of friction and corrosion.

Even the SR71, the most advanced plane imaginable in the 1950s, was hand-made. Gigantic sheets of titanium in fifty thousand ton presses still varied enough that essentially every one of the 32 SR71s created was unique and had to be maintained individually, often with parts that were hand-made to keep that specific plane flying. There was no simple “pop the bolts out and stick in a replacement part” for these things, even though they were at the absolute height of aerospace engineering right. Hand tuning was how technology worked.

The seed of the end of the age of hand-tuned machines was planted in Japan after WW2, when a quality control expert called Deming was shipped out there to help the Japanese rebuild their industry. At the time, Japanese industry was not a place to get quality production done. The industrial revolution had been resisted rather than embraced, and the distrust of foreign methods was legendary. Quite a few great ideas from the West had been absorbed by Japan, and some simply outright rejected. They did things their way.

So Deming’s radical ideas about workplace culture as the key to quality became firmly embedded in Japanese manufacturing culture, around the same time as the innovations of pioneers such as Soichiro Honda were taking root. Statistical process control — measuring everything that mattered to understand the real costs of operating a system — was relentlessly applied to create controlled environments which did astonishingly well at mass manufacturing consumer goods like cameras (resulting in great brands like Nikon and Canon) and pushing forward into previously unknown territory with microcomputer manufacturing at scale. You can’t build an artefact as complex as a microcomputer at affordable prices without essentially perfect components coming into the production line — any single fault will render the machine inoperable — and microcomputers are too complicated to take broken ones and rework them into repaired machines at affordable costs. It has to be done right the first time, there is no alternative.

You can’t build the modern, massively interconnected world from shoddy, unreliable parts. Think of the internet: if routers fell over as often as 1950s motorbikes, and had to be soldered by an experienced practitioner before they would work again — in short, if they worked like radios in the age of valve amps — the internet simply would not function. The odds of getting an intercontinental connection with not a single defective machine on the critical path would be approximately zero. The network as a whole would be too expensive to maintain.

Statistical Process Control is the steel spine that Deming built on. SPC figured out that people designing production systems have to be smart about what they measure, or the system will just produce what they measure, and they are measuring the wrong thing.

On this foundation, Deming figured out how to get people to understand the truths that SPC revealed: how to build a culture of truth inside of an organization so that they could learn from the statistical observations rather than burying them inside a feudal hierarchy rooted in information control and obscurantism to conceal trade secrets from the workers.

https://en.wikipedia.org/wiki/W._Edwards_Deming#Key_principles
  • Accountability came from statistical process control.
  • Transparency came from Deming’s emphasis on a culture of openness and clear communication.
  • Trust came from the non-violent, non-destructive correction of systematic errors, leading to goods and services that consumers could trust, because the people working together inside of organizations to produce those goods and services could trust each-other.

And this is how our civilization was made. It was made by teams of people who learned to trust each other enough to admit what is wrong, to correct systemic problems, and to work together in enormous numbers and at vast, unbelievable scale, to manufacture the complex artefacts required to run the operating system of modernity.

This process, this machine, the modern industrial supply chain is without a doubt the pinnacle of human civilization, the rich technical mycelium which gave rise to the moonshot and the curing of polio, the green revolution and everything else. It is everything from tractors to GPS satellites. It is the closest thing we have to a replicator.

Except for a very lucky few, most of us feel like things slipped off the rails somewhere in the past. Something went wrong with our culture. Exactly when, and how, and what went wrong depends on your point of view. The diagram which shows worker wages stop rising in line with worker productivity from 1971 is the thing I show people when I want to talk about “what went wrong”, but it’s only a symptom. Others might point to the Treaty of Versailles, or the ban on personal ownership of gold in America in 1933, or any one of fifty dozen points in history. But, Sometimes it seems like it does not matter how many good seeds we sow, what comes out of the ground is spears.

https://wtfhappenedin1971.com/

We have to negotiate with reality in a new way to get traction on the situation. The mechanisms we have been using to get good outcomes are not working very well: the mechanisms we expect to help the system self-correct all seem to point the wrong way at the wrong time, and the levers of change appear to be connected to the 8-track player in the dashboard, not to the wheels. We can change the music, but we can’t seem to change the direction. We are skidding.

Big Tech was supposed to help us with this, but it wound up largely as an outgrowth of the surveillance state. The blockchain was meant to fix this, but that political ambition has been almost entirely diluted out by the dreams of taking over the financial services industry (which might be a worthy short term goal, but let us not confuse it with saving the world). And saving the world is table stakes these days, as you might have noticed in the news.

We manufactured the wrong things, and we did not retool the rest of society to wisely use the output from the the wish-fulfilling tree of industrial mass production.

So let’s deal with manufacturing the wrong things first. Capitalism is pretty dumb: price signalling is a very limited stream of data between buyers and sellers, and learning in capitalism is notoriously slow. If I see a wheelchair on sale for $400 and I buy it, is that because I’m desperate for a chair RIGHT NOW, or because I look at the price and say “well, that’s a pretty good deal” and then get rid of my perfectly good old one? Would I have paid $500 for a model with a slightly better seat and a better color than institutional grey? Would I have paid $3000 for a carbon fibre wheelchair basketball model, were one available?

If all we’ve got is price signalling, the only way to move forward is to manufacture all the alternatives, advertise them widely and see what people buy. This is an evolutionary “bloom and prune” approach, and fields like market research which attempt to divine or anticipate buyers’ needs are often very inaccurate because people’s self-reporting about what they want is often very inaccurate. Just asking people what they want doesn’t cut it either. It is hard to fine-tune capitalism to manufacture what people want, and it is even harder when the advertising loop starts to take control of the process, not just telling people what is available, but actively trying to make them want things they did not previously want. Do you really want this thing, or do you want this thing because we made you want it? If we created the demand we are serving, are we helping anybody at all by meeting these imaginary needs?

That vortex, that infinite regress, has distorted the feedback systems inside of capitalism to the point where nobody knows what they want any more in any kind of solid, consistent, clear way. It’s created a huge and poisonous semantic fog which has taken away our ability to know ourselves, because the human mind was not made to reason clearly when fed 5000 ads per day. We evolved in a relatively slow moving, information poor environment without the written word. In a fast moving environment, dominated by marketing messages and skilfully composed advertising copy, and images produced by some of the most technically competent artists in the world, is it a wonder that we can’t think straight about what we want?

In fact, ironically, the only place statistical process control is applied to consumer behavior is targeted advertising, in which some of the best minds of our generation collude to gather vast portfolios of data about our personal lives, and use it to try and drive buying behavior without any fundamental model of people’s needs or wants, only their expressed preferences.

Is it a wonder that we’ve soaked up the entire capacity of the wish fulfilling tree of industrial mass production making fashionable junk that nobody needs, and still can’t seem to find a way to get everybody access to the drugs they need to stay alive, even basics like antidepressants or insulin?

We are squandering this plenty that statistical process control and quality control gave us, and it is killing us, and it’s killing the world.

Massive process engineering work has been done on the Production function of our society, over centuries. We have a name for it: the Industrial Revolution. Because it was a revolution. Quality control was also a revolution, but a quieter one.

In finance, something similar happened. The Investment function we discussed earlier also absorbed statistical concepts to manage how money moves around. Over time this became known as Quantitative Finance, and started to hoover up a disproportionate and frightening number of the brightest minds in physics and math. Enormous efforts have gone into building these systems, and they are uniformly amazing. They’re competing head to head, so there are winners and losers, but the actual quality of the work in quantitative finance is phenomenal.

But what about the consumption and waste functions?

Start with Waste. Has landfill gotten radically brighter and more efficient over the past 40 years? Maybe a little. But compare it to what has happened in manufacturing over the same period, and essentially our waste management is unchanged. There’s a lot of talk about recycling, and bins everywhere, but the actual reuse of that material in ways which prevent further raw materials being pulled out of the ground is a lot more complicated than people hoped when the recycling movement really got started. It’s too early to call recycling a failure, but all too often it just means dumping in poorer countries.

Recyclers are doing great work, but simply do not have the resources or support to combat the sheer scale of the waste. Although we have lots of incremental progress on pulling value out of industrial and post-consumer waste, are these systems really massively more efficient than what we had before? Do we measure, weed out variation, and make maps? Only here and there, and only in certain industries. Steel is pretty well recycled, plastic not so much.

But compared to the sophistication of the industrial processes that produced the plastic bottles we are throwing away, the recycling side is basically not even started.

Everything becomes significantly more valuable when doubt about the items in hand dramatically reduces. The best way of getting rid of waste is preventing it in the first place; durable goods which find homes with owner after owner after owner over time and never wind up in landfill is the best available option. But many objects — cars, bicycles, electronics — typically have a very rapid loss of value when they are resold. Even though eBay has put a lot of liquidity into second-hand markets, the transaction costs are still unacceptably high. Goods pile up or get thrown out (or dumped into charity shops, resulting in a really large loss of value and liquidity) rather than getting listed on eBay and resold to somebody who wants them. Selling things on eBay is hard, and half of that difficulty is describing what you want to sell, and pricing it appropriately. The other half of the difficulty is finding buyers: the asset liquidity problem, and that problem itself resolves down to search. If I’m looking for an item, and you call it “a great bass pedal” but do not list the actual model number, how am I to know if it’s what I am looking for? But, conversely, what if you list the model number, and I only know that I’m looking for a “great bass pedal”? Everybody is using their own words to describe things, and that semantic gap in itself reduces liquidity, and thence the value of the assets that are looking for new owners.

The information gap has an even more damaging form: the infamous “Lemon Market” which results when the sellers know more about items than the buyers. Without buyers having certainty about items, all markets are “lemon” markets. A “lemon” is a term used to describe a car which appears fine on the surface but has hidden mechanical problems, rendering it worthless. The higher the likelihood of “lemons” appearing among genuine goods, the more consumers are likely to price in the risk of buying one in the amount they are willing to pay for all items in the market. This drives the value of the entire market down, and is still very bad for a consumer when they end up with a “lemon” and bad for the environment when it’s scrapped. When there is certainty as to an object’s functionality, history and quality, the value which was previously depressed by the risk of buying a “lemon” is unlocked.

Consumption is hardly better. Yes, there has been progress, but the level of consumption has outstripped all imaginable process improvements in making that consumption efficient. Let’s talk about some of the measures taken.

So the first question is how do we know what we want. You know the general theme: your entire click stream is used to model who you are, so that advertisers can compete at auction to show you signals to control your behavior. And because we are not evolved to deal with these kinds of cognitive attacks (yet!) they are partially effective, enough to pay for progress and improvement in the fundamental techniques.

And let’s not forget, that’s the entire machinery of profit at Google and Facebook, and also a contributor to Amazon’s profits. How do they know what to recommend to you? A huge part of the economy of the internet is using statistical methods to understand and change consumption patterns, but in the crudest and least-effective possible way. “You get what you measure” remains the dominant fact of life, and measuring click streams and credit card purchases only measures one step of a four step process. We have optimized half way through investment, production, consumption, and waste, and no further. We should not be surprised that there are problems.

But, ugly and adversarial as the advertising attention-parasitism game is, and dangerous as these information dossiers on us all are, it is still an attempt to apply statistical process control to the consumption system, and it is still happening on a truly enormous scale. It takes exactly the same kind of reasoning which was used to make the manufacturing system efficient, and applies it to the consumption system, it just doesn’t push far enough into the consumption system to measure satisfaction. And it does not push into the waste system at all.

The targeted advertising system does what it does with a very partial model of the system it is trying to optimise, and only the most crude and short-term definition of its goals (evolutionary in the worst possible way, non-cognitive at the lowest level). But it does sell product, and it’s paying for the creation of enormous datasets about people and what we think they might want.

The problem is that it measures the wrong thing: measure spending, get spending. Measure satisfaction, measure progress towards our stated life goals, and maybe get those things instead. Price in environmental damage, and get another thing again. The problem is that spending is irrational, and behavioral economics factors thwart the eudaemonic potential to turn large scale datasets about people into the common welfare. We have made computers just smart enough to feed on us like attention parasites, but not smart enough to be good and faithful companions like dogs or horses. I cannot yet meaningfully say to Google “find me a good book to read, but make it a little outside of my norm, the last few suggestions have been a trifle timid” and get any useful intelligible response, but the damn thing won’t stop showing me adverts for books it wants me to read. The stupid system is incapable of partnership, it only knows how to hustle and distract us. We have not gone far enough to get positive results, only negative ones. The system is building momentum, but it is still below the threshold of revolutionary change.

Let’s look at other areas where we have large-scale successful attempts to use statistical process control to optimise consumption. Uber tries to put cars where it anticipates there will be riders. It uses price signalling to encourage drivers to turn up during periods when it expects things to be busy. Uber plays the game. Still they seem to have wound up in the same trap as (for example) Apple hardware manufacturing: a truly great service for some people, at the expense of the labour rights of others. The algorithms optimized resource allocation in the pursuit of everyday low prices (or at least good quality goods which defy our expectations about what phones and tablets can be like, year after year after year). But these systems still wind up treating human beings like machines at every level, and this trend has to be identified and banished before we wind up in Marshall Brain’s vision of dystopia.

Amazon is optimizing what is in the warehouses closest to you, based on the ability to get most of what you order to you same day or next day. This is a fantastic example of using statistical process control to optimize outcomes and serve people’s needs: whatever it is you bought, it’s more valuable to you if it arrives quickly. This is an unmitigated good, again extracted at a very heavy social cost: Amazon warehouses really have picked up the reputation of treating people like a cheaper version of machines. Amazon would certainly automate all the way, if they could.

And that’s basically it for using statistical process control and quality control to optimise consumption. We haven’t made any strides on the scale of the industrial revolution in the consumption system. Not even close.

Consider the amount of things we buy in the course of our lives for what amounts to experimenting with our identity — goods we purchase to understand ourselves better, or to foment personal growth. You may want to take up the guitar, try your hand at fly fishing, or start learning Tae Kwon Do. As a beginner, you often have no idea what the best kit is to start off. So you end up spending large amounts of time tracking down reviews and recommendations, many of which are contradictory. You wind up either getting the most expensive equipment presuming that price equals quality, or the cheapest with the best overall reviews, knowing you’ll have to replace it if the hobby sticks and you become an aficionado.

Furthermore, this process leaves residue. Each of us has that stash of stuff sitting unused in closets, attics, and garages; the remnants of hobbies and identities which didn’t quite fit, and were set aside. We may manage to move some of it along by selling it online or at a yard sale, but for the most part it all just sits there. The transaction costs of getting rid of it are too large for us to take action: the stress of making the decision to sacrifice a slab of our investment and just sell the damn thing, the time it takes to list on an auction site, the physical logistics of posting it to a new owner, and managing the customer service overheads involved in the entire process often leave the goods (and therefore the capital they represent) stranded. The other approach, just writing them off and throwing them in the dump, seems wrong — both a waste of money, and of the materials embedded in the objects. So instead of doing the rational thing and getting rid of it, we wind up using nearly every square inch of the Boomer generation’s basements, attics, and closets as a sort of informally specified, unsearchable, distributed warehousing solution as the massive superabundant flow of goods from our hyper-optimised production system hits the analogue slackness of our consumption systems, and simply pools in a huge lake of underutilized or obsolete things. There are millions of metric tons of this kind of waste in America, and it all has value — if only we can find it.

Mattereum’s system will aggregate expert opinions about objects for ease of consultation. Furthermore, we have a new mechanism for incentivizing these experts to put in the time and energy that it takes to express their opinions clearly. If accomplished guitarists can weigh in with their opinions of how a particular guitar fares as a beginner’s instrument, for example, consumers can wade through the advertising hype and get informed answers to the questions they’re really asking when deciding what to buy. But everyone going out and buying their own stuff just to try out is part of what got us into our current situation in the first place. If we think of our personal caches of underutilised goods as a sort of poorly organised matter network, of which our closets and garages are just one node, then we can begin to organise this network to make the best use of a wealth of untapped resources in our own backyards. Look up the kit that is the best match for what you’re looking for, and then rent or buy it from your neighbour up the road who has one going spare. If all of these goods were in the Mattereum ecosystem, then the groundwork is laid for both an efficient sharing economy as well as an agile market for second hand goods.

And this is good news not just for consumers, but for producers. If there is a robust, healthy, friction-free secondary market for guitars, cameras, bicycles, even cars, people are much more likely to buy the best they can afford knowing full-well they can easily resell it at a fair price as soon as a better model comes out, or they no longer need it. Many professional photographers, for example, operate this way already. They use the best possible equipment and upgrade almost automatically when better gear comes out, because there’s good enough liquidity in the second hand markets for good quality cameras that they are taking very little risk buying new, high quality equipment. Good for Nikon, good for Canon, good for Sony, and the photographer, and the people buying their photographs. Efficient secondary markets are nobody’s enemy: they just increase the average quality of goods available to everybody. Only the real trash gets pushed out of having value by these markets.

To make this vision come true, we need a new category of software.

The production systems of the world run on Enterprise Resource Planning (ERP) systems, of which SAP and Oracle are probably the two best-known examples. Similar systems exist in the world of finance to manage capital inside of banks, and to allocate resources in private equity firms. This is the software which runs civilization’s arteries and veins, its digestive system and its lungs. It’s the nervous system of industrial capitalism, and without it, we would almost all be destitute. But these systems are corporate, intimately tied to the Investment and Production phases of society, but only very weakly tied to consumption and waste management. They are, essentially, direct descendants of the mainframe paradigm: one big computer that rules the whole organization. And these systems interoperate only with great reluctance; it’s not a big, interwoven flexible mesh of big ERP systems seamlessly talking to each-other to make optimal decisions. It’s all still largely stuck in the mainframe phase, on arcane standards that are impossible to parse, and worse to debug. In short, these systems are due for an upgrade.

What we need is ERP for the People.

We need smaller, more flexible software systems to help individuals manage the same kinds of tasks that ERP systems handle: physical assets, time, money, commitments and more, as integrated systems. We would all really benefit from having tools that bring the power of knowing what you’ve got, where you have it, what you paid for it, and what it’s worth to somebody else right now. Imagine how much it would change if it was all at our fingertips in a series of dapps which help us optimize our personal relationship with matter itself, mediated by the marketplaces we all participate in, plus new marketplaces for information about the quality, provenance and value of physical objects.

Our working title for this model is Effective Abundance Platforms: platforms which help us manage our relationship to the abundance that industrial capitalism produces, while optimising the hell out of the inefficient capital allocation mechanisms which are represented by inefficient purchasing and reselling behavior among consumers. It’s clean, it’s green, and we think, with Mattereum in the lead, it could be extremely profitable as a new class of businesses.

Our core argument is that everything is underpriced because buyers are constantly hedging against imperfect information in their purchasing decisions: in short, that all markets are “lemon markets”. Even if the thing you buy is perfectly described, you can still be hurt by what you don’t know: there was a better one available, or a better one is released next month. We are constantly trying to lowball our purchases to manage the risk of making mistakes.

This psychology applies as much to houses, cars, and industrial machinery as it does to consumer goods and trinkets. Fear-based behavior from buyers reduces overall economic efficiency in a number of ways.

For example, buyers will:

  • Trade at a discount from perceived value (expensive things are cheap on eBay partly because buyers do not trust what they are buying will be what they receive, so prices are depressed)
  • Hesitate (reducing liquidity and harming cash flows)
  • Introduce expensive middle men to reduce risk (for example, multiple third parties in a real estate deal exist to certify facts about the house to the buyer, and all their fees reduce the price the seller can feasibly charge for the house)
  • Increase “trade gravity” (people tend to trade with people they are culturally close to, rather than the ones it is economically most efficient to trade with if we ignore cultural factors because we imagine we have more control when dealing with neighbours)
  • Buy from brands at a premium because they trust the brand on matters like quality assurance, design, and fitness for purpose (premium price behavior)

All of this is economic inefficiency which can be squeezed out of the global trade system if we can use technology to reduce the uncertainty of trade.

Better information leads to more efficient markets, and higher prices for assets with higher resolution data.

VISA is an august institution. It is much older than most people think: it was started in 1958. VISA’s history is absolutely fascinating, and extremely clear, precise and bold visions of the future powered VISA’s expansion and growth to world domination.

VISA, as an organization, is probably the closest precursor to blockchain technology. It exists to enable trade, globally, and does so by mitigating a set of risks which make it harder for people to buy and sell across the world. While it did not have the explicit political vision of Bitcoin, still the world that VISA seemed to be creating in the early days was much the same world: endlessly fluid, seamless, point to point transactions around the globe. That was the vision, anyway.

One of the key contributors to the success of VISA is their comprehensive strategy for reducing perceived consumer risk when using VISA to make payments. By providing risk mitigation for buyers living with uncertainty, VISA does succeed in facilitating global trade, particularly on the internet.

Because VISA charges such a high fee (2%+) and has massive market power, they can afford to provide dispute resolution to buyers, and enforce sanctions on sellers (the infamous chargeback), in essence acting as a global small claims court. Relative to small businesses who are dependent on being able to accept VISA cards to continue in business, VISA is parasovereign. Access to justice on even such a rough-and-ready basis as VISA’s customer service reduces a buyer’s perceived risk, so people will pay for goods online with credit cards knowing that if they are defrauded they can get their money back, with the entire system being governed and overseen by VISA, Mastercard, and their peers (at a B2B level, including SWIFT.)

This dispute resolution plus insurance package is extremely powerful for getting trade to happen where it otherwise would not, specifically because it protects buyers from a range of risks, including some classes of information inequality. VISA makes its living from sellers’ willingness to pay high transaction fees; their increase in total transaction volume from accepting VISA more than compensates for the transaction fees VISA charges on those transactions. This covers many inaccuracies in product descriptions; people can always say “goods were the wrong color, accept my product return or I will call VISA to arrange a chargeback.”

But if we could create the right kind of markets for truth about those facts, we could eliminate those errors, and correspondingly reduce global transactional friction. And at these scales, every little bit helps.

VISA, and all other money transmission systems that offer bundled services, makes a living by getting trade to happen where trade would otherwise not. It provides a bundle of services to make this happen. The power of the blockchain allows bundles of services like VISA’s to be disaggregated into marketplaces, leaving a decentralized, competitive marketplace where component services can be assembled into a system more efficient and powerful than the existing financial architecture has ever been. This is significantly beyond the scope of this article, but it’s news to nobody: including VISA.

VISA itself recognizes the potential transformative power of the blockchain. The new VISA B2B Connect service uses Hyperledger to make more efficient international payments a reality, in theory competing with SWIFT. But a reasonably well designed blockchain trade system need not differentiate between B2C and B2B users; the underlying technology is secure enough to handle both use cases on the same backbone, as is natural to the decentralized paradigm.

All of these technical trends converge on the same vanishing point: a world in which money flows around the world as easily as information. Mattereum thinks that model is likely to be broader: information, money, goods and services flow around the world as easily as information.

But to get there, it’s important to understand how VISA operates, and what lessons it has for us as we come to our core challenge: redesigning the global economy so we have a planet worth living on in a hundred years.

Now let’s look at VISA in more depth to understand how they have become such a massive global financial infrastructure player.

The VISA model bundles six services:

  • Identity (for both buyer and seller)
  • Credit
  • Currency conversion
  • Payment rail
  • Dispute resolution
  • Transaction insurance

The blockchain ecosystem is building out a service architecture which roughly parallels VISA’s categories of functions:

  • Identity (Sovrin, uPort, Civic, Mattereum)
  • Credit (MakerDAO, Ethlend)
  • Currency conversion (exchanges, Bancor)
  • Payment rail (Bitcoin, Ether, DAI from MakerDAO)
  • Dispute resolution (Mattereum)
  • Transaction insurance (Mattereum, Etherisc)

So the argument can be made here that the blockchain community are building out a “decentralized VISA.” Not an unworthy goal, as VISA and Mastercard equal upwards of $30 billion of revenue per year on more than $10 trillion of transactions. Additionally, given that blockchain payments are generally considered to be non-reversible, some businesses may greatly prefer blockchain payment solutions to address the problem of unreliable invoicing.

However, the credit card paradigm does not touch vast areas of payments; mortgages, B2B transactions (perhaps 4 times the size of the B2C economy) and larger payments in general are out of scope for the credit card. But the emerging DeFi (“decentralized finance”) model does not distinguish between B2B and B2C services, and fully supports P2P transactions on exactly the same basis. It’s all one. The new emerging architecture is scale-free: trade is trade is trade.

There’s another source of trouble in the existing system that the new system will fix: human error. High error rates, manual re-keying of invoice details, lack of any kind of meaningful “API economy” for automated provisioning of goods and services and so on adds up to a much larger opportunity than competing for the credit card in B2C financial transactions.The entire process of invoicing and processing large transactions is in desperate need of optimisation. SWIFT processes over $5 trillion per day, (at far lower margins than VISA, of course). But all of those transactions will be associated with labyrinthine internal bureaucracies, fundamentally ruled by the big four audit companies who make a living unpicking the natural errors — and occasional frauds — that occur when you have humans in the loop manually entering invoices into databases. Imagine the transformation possible in this space as precise, clear, machine-readable descriptions of goods and services (backed by guarantees linked to escrowed funds, for example) reduce the error rates on these transactions to near-zero over time.

The trajectory for the blockchain industry has to be towards automating error-free B2B and B2C transactions, using triple entry bookkeeping concepts to unpick the invoicing maze and cleaning up the manual processes which exists at the boundary between almost all large organizations. Putting B2B, B2C, and P2P transactions on exactly the same backbones, and reducing the friction of operating over international boundaries to near zero is going to unlock genuinely world-changing amounts of wealth.

And we need to squeeze every last grain of efficiency that we can out of the global economy, because people are still hungry, and structural waste on a finite planet is the enemy of everything that lives. If the internet has a purpose, if the blockchain has a purpose, this has to be part of it: we aren’t just fighting against authoritarianism, we are also fighting against entropy.

Food rotting in the back of the warehouses does not have to happen. We just need efficient systems to connect hunger to food, and at least half of that problem is just bad software which harms the sellers as much as the hungry buyers.

We are all on the same side against waste, and bad software. It’s all of us, against entropy.

Mattereum started to create a “supreme court of the internet” for hearing disputes related to the use of Ethereum and other smart contracts in real world trade. This business model uses the provisions of the 1958 New York Convention on Arbitration to establish a private court which users can opt in to for their dispute resolution by including simple boilerplate text in their contracts. We saw this (and still do!) as a vital missing component in getting world trade on to the blockchain platforms that are emerging.

Many such specialized courts already exist for industries like construction or ship-building, handling hundreds of billions of dollars of disputes every year, so why not for the blockchain space? Most of our innovations in this area relate to technical evidence handling, court procedures, and cost control. Importantly, the awards made by courts of this type are easily enforced internationally. But blockchain adoption in the real world has been slow, and the dispute volume to support such a court does not exist yet. We were a little early.

We then pivot Mattereum into its second phase: the initial arbitration-centric “supreme court of the internet” model, which is well-suited to providing legally binding dispute resolution services for large volume commercial transactions, pivots to become the “smart property register”, in which we figured out how to apply these concepts to much smaller transactions by narrowing focus to a specific subset of disputes: disputes about the authenticity or qualities of a physical object. Mattereum does this by taking a whole set of disputes about point-of-fact issues, and moves them out of litigation-style dispute resolution — adversarial, multiple parties, win-lose, complex burden of proof type decision-making, fault-finding etc. — to insurance claim style dispute resolution. We accept that insuring against the damage done by human error and occasional low-level fraud is necessary for function in the real world. Trade needs this. VISA proved that.

We then narrow focus further to the first component of the Smart Property Register: the Mattereum Asset Passport, which is essentially a Self Sovereign Digital Identity for a physical object. An Asset Passport can optionally include a Digital Twin of the object.

An enormous number of disputes in the real world are about the attributes of objects purchased, including secondary situational factors like delivery time. But the basic dispute frameworks are that the thing was not as described, or thing was not fit for purpose and has to be returned. Accurate, truthful, complete information wipes out entire sets of disputes, bringing down the overall system costs for dispute resolution across all trade. It is like the difference between doing business in a clean vs. a corrupt economy: there’s a threshold past which things just get easy, and the economy really beings to fly. That’s what we envisage doing for the trade in physical assets.

The more we can get people to tell the truth about their offers, the more efficiently the overall economy runs. We have to reshape the incentive landscape to get full disclosure about products, and the Mattereum Asset Passport achieves this.

Essentially, we want a paradigm where, when something goes wrong, people do the equivalent of swapping insurer information, and moving on with their day. We want a situation in which the normal accidents of everyday trade can be covered at a financial level, without requiring complex dispute resolution procedures in cases without contentious dispute.

Mattereum’s business model depends on the research, development, and service design we did during this phase. The arbitration model we built to provide relatively affordable global dispute resolution for smart contracts also backs up the dispute resolution mechanisms used in the smart property register. Small disputes are handled using an insurance-type model, and larger disputes or problematic misrepresentations are escalated to our other dispute resolution forums. Without this model, disputes about blockchain smart contracts and oracles would have to be handled in regular courts, which would be unfeasibly slow and expensive.

Justice has to be fast and economical if it is going to support a low transaction cost blockchain economy.

One critical area of uncertainty, which adds friction to trade, is uncertainty about product specifications, both for newly manufactured goods, and for secondary markets like eBay.

We have accumulated near-infinite data about people and their behavior in the past 20 years, far, far more than is really safe, necessary, or appropriate. However, we have singularly failed to make a similar accumulation of data about products; neither Amazon nor eBay currently permit me to shop for a laptop by a specific port configuration (“full sized HDMI port, two USB 3.1 ports, ethernet port”) never mind by the force-distance profile of the laptop keys to tell how it will feel to type on it. We still can’t buy clothes that fit online.

These benefits will be cumulative. Why should I have to guess whether a TV will fit in the back of a car before I physically pick it up and try? The data exists: every one of these objects had a digital representation that it was manufactured from, but the data disconnects in the economy just cause massive inefficiencies at every hand and turn. Why can’t I tell Uber the size of the TV set I want to move, and have their software automatically provision the right car?

The “Digital Twin” paradigm ought to be the standard to which everything is produced. We should always be able to access a high resolution digital copy of our property — size, shape, materials, functional properties, and so on — so that we can always access complete information about what we own. Mattereum will establish the new market paradigm to get those digital twins built, bottom-up and grass roots style where necessary. Once we have those digital twins, we can start automatically searching for synergies in matter: what fits with what, what interoperates with what, what will match what. Color, size, shape, fit, technical standards, you name it. Matter is worth more once it is searchable, and computers can figure out its affordances for us. “Yes, this TV will fit in the back of your car.” I’d pay to know that before I picked it up. So would you.

More than ever we have to stretch global resources: more people with more demands for more things, on a planet that is already creaking from ecological strain. Better information means better decisions, lower friction, and reduced risk. It means more efficient rental and second-hand markets, efficient enough that they may explode into a whole new kind of utility (think Uber and AirBnb), and all this adds up to a more efficient fundamental economy. There is no reason for archaic property rights norms, established in the medieval or pre-medieval period to serve a struggling 21st century society properly. We need to make matter work more like information.

Instead, we need a vastly more liquid system of property rights. Not simply tokenization and securitization of the ownership of assets, but a transformed relationship with matter: automated scheduling and provisioning, open options (“I need a sewing machine for two days any time in the next six weeks”) and so on.

We can stretch existing capital assets to serve many, many more people. This serves both commercial and ecological imperatives.

So, when all is said and done, all theory aside, what does it do?

The Mattereum process is three parts: Asset Passports, Automated Custodians, and the Smart Property Register. The Automated Custodian is the technical/legal machinery for doing instant property ownership transfer almost anywhere in the world: an atomic swap for property. We aren’t there yet, but we are working hard on it. The Smart Property Register is for contract composability: it’s how you’d put your house into a pool for a Blockchain Airbnb based on sublease clauses in your rental contracts. Again, that’s over the horizon: the defi ecosystem has to mature a bit before that has genuine utility, although MakerDAO’s ecosystem is rapidly approaching the point where this functionality would be useful!

So that leaves the Mattereum Asset Passport, our first product.

What is the Mattereum Asset Passport? It’s a domain name for physical matter. Is is the abstraction required to connect ordinary physical matter to the internet, in the same way that domain names were the abstraction layer required to connect existing brands, concepts and information assets to the internet.

It is literally an Ethereum smart contract which serves to collect together all the relevant identification information for an object. This information is presented as a second series of smart contracts, which sell very specific indemnification contracts that verify that the information about the object is correct, and pay out if it is proven to be in error. The Mattereum Asset Passport is sort of like a microDAO surrounding an object: a plurality of people all make claims about an object and its provenance, and they can all stake their money on the accuracy of their claims. Anybody that wants to take them up on those promises pays for the privilege. The more people are relying on your data, the more money you get paid. But people can make claims, and invite people to rely on those claims, cooperatively or competitively. It is a market for facts about things; the necessary market infrastructure to effect a transformation in how we approach the material world.

That paradigm applies at every level of trade, from Magic the Gathering cards up to oil tankers.

Our initial alpha relies on quite a few Old World fiat abstractions but as time passes every level of this structure can be automated. Payments go from fiat-enforceable promises, to escrow accounts, to third party judicial release escrow accounts, up to proofs of insurance and reinsurance, over time. Likewise, we start by using fiat identity in the same manner as would be typical for KYC, but will upgrade to uPort, SOVRIN and other decentralized identity solutions as the technology matures.

In the long run, it will be all digital.

So we present you with an example Asset Passport. Our Head of Ontology spends quality time on WW1 battlefields in uniform, reliving the past, and coming to grips with it. On one of these expeditions, he recovered an artefact, and we are documenting more than a century of this item’s history using Mattereum Asset Passports.

I hope you will find that this practical example puts together the whole idea nicely. It’s just the start.

Exploring the Asset Passporting Process, By Dr James Hester — Head of Ontology & Provenance, Mattereum

After serving as Royal Armouries Curator of Collections at the Tower of London, and later completing my PhD interpreting how medieval arms and armour was used by examining traces of battle damage, I joined the team at Mattereum to put my training in understanding and documenting objects to a fascinating new purpose.

In the world of art and antiquities, a curator or a dealer will seek to compile everything that it is possible to know about an object, since doing so will not only enhance and reinforce its cultural value, but also (especially for the dealers) its monetary value. A doodle on a napkin may not be very interesting or valuable to anyone. However, when we realise that it was drawn by Picasso as a gift to a friend or to pay his bill at a café, then suddenly an otherwise insignificant object becomes very significant indeed. The same is true for any object. Lacking sufficient knowledge about it, a person might fail to appreciate its utility or value. But by gathering together all of the data regarding that object into one place, we can make much more informed decisions about the things we use, and the way we use them.

One particularly important questions is, of course, how to tell whether the doodle on the napkin is actually by Picasso, or if someone is trying to profit from making you believe that it is. To date, the authenticity of an object — when there is no one currently alive who bore witness to its manufacture — is determined in many sectors by experts. As consumers, we are told that the opinions of these experts can be trusted due to their reputation in the field, gained from years of experience in dealing with a particular class of object. But even the most knowledgeable expert can make a mistake, or a charlatan may attempt to pose as an expert. And when this happens, apart from some damage to the expert’s reputation, the buyer often has little to no recourse to compensation for the error or misleading information.

The smart contracts contained in the Mattereum Asset Passport provide a solution to this asymmetric dynamic. Expert opinions regarding all aspects of an object are still sought and gathered together, but with an added layer of protection for buyers in the form of indemnities which must be signed by anyone providing such an opinion. Furthermore, experts must put some skin in the game, in the form of a sum of money which they are bound to pay out if their statement turns out to be false. So if an assertion made about an object is found to be untrue, the buyer is compensated: it’s true, or you can sue.

So, how do we do it?

To show how all this works, let’s follow an object through the process of receiving a Mattereum Asset Passport.

Our object is this seemingly insignificant piece of mangled brass. It is, in fact, a spent rifle cartridge dating back to the early days of the First World War. A surprising amount of information can be extracted from this piece thanks to a combination of numerous factory marks and the context in which it was found. It’s a perfect candidate to showcase the range of information an Asset Passport can contain, and how we go about documenting and supporting it.

The specific name of this type of cartridge can be determined through consulting either a subject expert or any number of authoritative reference guides. The places involved in its manufacture, and even the dates (French cartridges very helpfully display not only the year of manufacture, but also the quarter of that year) can be identified thanks to the numerous factory marks stamped into the rim. In addition to its current measurements, we also know its original, factory new measurements since, being a pattern-produced object, this is well documented. So with just the object itself, combined with a bit of light homework and an inspection of its current condition, we have a substantial description of our cartridge.

Portion of the cartridge’s data sheet

All of the information here is supported by a combination of signed identification statements by experts and references to authoritative reference sources. These are the keystones upon which are built the assertions that the above data is true.

Section of Mattereum’s Certifier Contract (which I, as the source of the data, would sign) confirming the description of the cartridge.

So now that we know, in general terms, what the object is, we can move on to answering the second important question: where has it been?

Tracing an object’s provenance — its history of ownership ideally all the way back to its creation — begins with the present and works backwards from there. Understanding where an object has been is essential for a number of reasons. Returning to the napkin which may or may not contain a Picasso drawing, it can mean the difference between a piece of tissue or a valuable work of art. For manufactured goods, it could mean the difference between a properly made product and a potentially faulty knock-off. A pair of limited edition Air Jordans is a very different object from a pair of the same which Jordan actually wore when the Bulls won the championship. Provenance documentation also provides information about an object’s past which could have important ramifications. If the object was stolen, created using prohibited materials, or produced in illegal or unethical conditions, unaware owners might not be able to escape trouble by simply pleading ignorance.

For our cartridge, current ownership is easy to determine: it forms part of my personal collection. As a member of a living history group which portrays the life of soldiers in the First World War, I have the honour to visit the Western Front regularly to take part in ceremonies commemorating the conflict and those who took part in it. On one such visit to the Somme this year for the memorial to the start of the infamous battle on 1 July 1916, I discovered this cartridge in a pile of soil excavated as part of the works being done on the site where our encampment was located. So in addition to my statement that the cartridge was discovered, lawfully excavated, and lawfully in my possession, I have the support of a similar statement made by an independent expert witness who was present when I excavated the object.

But our object’s story does not end there. As it happens, the area of the Somme where the cartridge was found (La Boisselle, on the outskirts of Albert), was only occupied by the French Army for a period of four months before the British took over this part of the Western Front for the Allies. Furthermore, military records tell us that there were eight units of the French Army present in La Boisselle during this time. So by virtue of where our cartridge was found, we can confirm with authority that it was fired between September 1914 and January 1915 by a French soldier from one of eight units, which led it to be discarded and, over a century later, recovered by a history buff paying homage to their memory.

Left: French soldiers of the 118e régiment d’infanterie at La Boisselle (1915). Right: Members of the 10th Essex Regiment WW1 Living History Group with French reenactors at La Boisselle for the 2019 commemorations of the Battle of the Somme (I’m the chap farthest right).

We now have all of the information regarding the object gathered together. We convert the data into XML format, each statement of identification and provenance being treated as a separate and distinct data point. These data points, along with reference photos documenting all parts of the object and statements affirming the existence of all appropriate supporting documentation (as well as digital copies of relevant documents) are uploaded to an IPFS server. The unique identifiers created by this process to represent the sum total of all data on the object, as well as the assertions of the validity of the statements and the smart contracts laying out the modes of recourse should any information turn out to be false, combine to form the Mattereum Asset Passport. In the cases where there are privacy concerns, the existence of certified data can be proved by a hash or a series of hashes placed on chain, without the data itself being made public.

Above you can see what parts of the user interface for our cartridge’s Mattereum Asset Passport look like. All of its data has been entered as XML and is reproduced in an easily accessible format. It is also possible to view the certification details of assertions made about the object.

Upon viewing each assertion, and the relevant supporting documentation, users have the opportunity to purchase an indemnity, housed in a smart contract, offered by the certifier for a set fee.

With the click of a button, the smart contract activates, processes the transaction, and buyers can now enjoy an unparalleled level of protection from misinformation regarding the things they buy.

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